
How Data Scientists Work Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?
In recent years there has been an increasing trend in which data scienti...
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AutoML using Metadata Language Embeddings
As a human choosing a supervised learning algorithm, it is natural to be...
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Invertible Gaussian Reparameterization: Revisiting the GumbelSoftmax
The GumbelSoftmax is a continuous distribution over the simplex that is...
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One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples
Modern image classification systems are often built on deep neural netwo...
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FaceShapeGene: A Disentangled Shape Representation for Flexible Face Image Editing
Existing methods for face image manipulation generally focus on editing ...
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ThemeMatters: Fashion Compatibility Learning via Theme Attention
Fashion compatibility learning is important to many fashion markets such...
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SketchGraphs: A LargeScale Dataset for Modeling Relational Geometry in ComputerAided Design
Parametric computeraided design (CAD) is the dominant paradigm in mecha...
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Noise2Blur: Online Noise Extraction and Denoising
We propose a new framework called Noise2Blur (N2B) for training robust i...
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Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling
We consider the problem of inferring the values of an arbitrary set of v...
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Unrestricted Adversarial Attacks for Semantic Segmentation
Semantic segmentation is one of the most impactful applications of machi...
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Stacked SemanticGuided Network for ZeroShot SketchBased Image Retrieval
Zeroshot sketchbased image retrieval (ZSSBIR) is a task of crossdoma...
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Learning Your Way Without Map or Compass: Panoramic Target Driven Visual Navigation
We present a robot navigation system that uses an imitation learning fra...
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Learning to Compose Dynamic Tree Structures for Visual Contexts
We propose to compose dynamic tree structures that place the objects in ...
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Weakly Supervised Attention Networks for FineGrained Opinion Mining and Public Health
In many review classification applications, a finegrained analysis of t...
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Zero Shot Learning on Simulated Robots
In this work we present a method for leveraging data from one source to ...
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Controversial stimuli: pitting neural networks against each other as models of human recognition
Distinct scientific theories can make similar predictions. To adjudicate...
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COVID19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
To combat COVID19, both clinicians and scientists need to digest the va...
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Towards Understanding Fast Adversarial Training
Current neuralnetworkbased classifiers are susceptible to adversarial ...
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Practical Deep Reinforcement Learning Approach for Stock Trading
Stock trading strategy plays a crucial role in investment companies. How...
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TGAN: Deep Tensor Generative Adversarial Nets for Large Image Generation
Deep generative models have been successfully applied to many applicatio...
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Unsupervised Deep Tracking
We propose an unsupervised visual tracking method in this paper. Differe...
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ESMAML: Simple HessianFree Meta Learning
We introduce ESMAML, a new framework for solving the model agnostic met...
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Segmentation with Residual Attention UNet and an EdgeEnhancement Approach Preserves Cell Shape Features
The ability to extrapolate gene expression dynamics in living single cel...
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AlphaGAN: Fully Differentiable Architecture Search for Generative Adversarial Networks
Generative Adversarial Networks (GANs) are formulated as minimax game pr...
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PointHop: An Explainable Machine Learning Method for Point Cloud Classification
An explainable machine learning method for point cloud classification, c...
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MultiTask Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics
We present an endtoend statistical framework for personalized, accurat...
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Rethinking Generative Coverage: A Pointwise Guaranteed Approach
All generative models have to combat missing modes. The conventional wis...
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Individual predictions matter: Assessing the effect of data ordering in training finetuned CNNs for medical imaging
We reproduced the results of CheXNet with fixed hyperparameters and 50 d...
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AutoKnow: SelfDriving Knowledge Collection for Products of Thousands of Types
Can one build a knowledge graph (KG) for all products in the world? Know...
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Adaptive SampleEfficient Blackbox Optimization via ESactive Subspaces
We present a new algorithm ASEBO for conducting optimization of highdim...
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General Partial Label Learning via Dual Bipartite Graph Autoencoder
We formulate a practical yet challenging problem: General Partial Label ...
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Hierarchical Long ShortTerm Concurrent Memory for Human Interaction Recognition
In this paper, we aim to address the problem of human interaction recogn...
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Moment Matching for MultiSource Domain Adaptation
Conventional unsupervised domain adaptation (UDA) assumes that training ...
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FullyFeatured Attribute Transfer
Image attribute transfer aims to change an input image to a target one w...
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Substituting Gadolinium in Brain MRI Using DeepContrast
Cerebral blood volume (CBV) is a hemodynamic correlate of oxygen metabol...
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Realtime Universal Style Transfer on Highresolution Images via Zerochannel Pruning
Extracting effective deep features to represent content and style inform...
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Smoothed Analysis of Online and Differentially Private Learning
Practical and pervasive needs for robustness and privacy in algorithms h...
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TreeStructured Recurrent Switching Linear Dynamical Systems for MultiScale Modeling
Many realworld systems studied are governed by complex, nonlinear dynam...
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Deep Reinforcement Learning for Intelligent Transportation Systems
Intelligent Transportation Systems (ITSs) are envisioned to play a criti...
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Bayesian Tensor Filtering: Smooth, LocallyAdaptive Factorization of Functional Matrices
We consider the problem of functional matrix factorization, finding low...
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SemEval2015 Task 10: Sentiment Analysis in Twitter
In this paper, we describe the 2015 iteration of the SemEval shared task...
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Valid Causal Inference with (Some) Invalid Instruments
Instrumental variable methods provide a powerful approach to estimating ...
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Structured Monte Carlo Sampling for Nonisotropic Distributions via Determinantal Point Processes
We propose a new class of structured methods for Monte Carlo (MC) sampli...
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Image Outpainting and Harmonization using Generative Adversarial Networks
Although the inherently ambiguous task of predicting what resides beyond...
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(Sequential) Importance Sampling Bandits
The multiarmed bandit (MAB) problem is a sequential allocation task whe...
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Multilevel Multimodal Common Semantic Space for ImagePhrase Grounding
We address the problem of phrase grounding by learning a multilevel com...
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Hierarchical Macro Strategy Model for MOBA Game AI
The next challenge of game AI lies in Real Time Strategy (RTS) games. RT...
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PixelAttentive Policy Gradient for MultiFingered Grasping in Cluttered Scenes
Recent advances in onpolicy reinforcement learning (RL) methods enabled...
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Two models of double descent for weak features
The "double descent" risk curve was recently proposed to qualitatively d...
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How many variables should be entered in a principal component regression equation?
We study least squares linear regression over N uncorrelated Gaussian fe...
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Located In New York City, The School at Columbia University is a Private K8 Day School serving neighborhood families and Columbia University employees.